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Proceedings Paper

Multistage adaptive search vector quantization for image compression
Author(s): Wail M. Refai
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Paper Abstract

This paper presents a new multi-stage adaptive search (MSAS) vector quantization algorithm for image compression. It permits improved solutions which approximate the exhaustive- search multistage solution. The standard multi-stage vector quantization algorithm had the advantage of simple structure and low complexity. However, the performance degrades rather rapidly when the number of stages increases. Our algorithm has the same advantage as the standard algorithm, but the performance is much higher and also higher than the tree/full search vector quantization. The adaptive search algorithm can also be applied to the tree-search vector quantization (VQ). Tree adaptive search algorithm is a very powerful algorithm. The larger the tree-structured codebook, the better the performance of tree adaptive search VQ algorithm. However, when the codebook size increases, the codebook generation complexity and the required codebook memory increases exponentially too. A multi-path algorithm is also presented in this work. It can improve the performance of multi-stage adaptive/non-adaptive search VQ. It only increases the complexity of encoder. For the decoder, it is identical to the multistage algorithm.

Paper Details

Date Published: 7 June 1996
PDF: 6 pages
Proc. SPIE 2751, Hybrid Image and Signal Processing V, (7 June 1996); doi: 10.1117/12.241996
Show Author Affiliations
Wail M. Refai, United Arab Emirates Univ. (United Arab Emirates)


Published in SPIE Proceedings Vol. 2751:
Hybrid Image and Signal Processing V
David P. Casasent; Andrew G. Tescher, Editor(s)

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